RT info:eu-repo/semantics/article
T1 A taxonomic look at instance-based stream classifiers
A1 Gunn, Iain A.D. .
A1 Arnaiz González, Álvar
A1 Kuncheva, Ludmila I. .
K1 Machine learning
K1 Stream classification
K1 Instance selection
K1 Prototype generation
K1 Concept drift
K1 Computer science
K1 Informática
AB Large numbers of data streams are today generated in many fields. A key challenge when learning from such streams is the problem of concept drift. Many methods, including many prototype methods, have been proposed in recent years to address this problem. This paper presents a refined taxonomy of instance selection and generation methods for the classification of data streams subject to concept drift. The taxonomy allows discrimination among a large number of methods which pre-existing taxonomies for offline instance selection methods did not distinguish. This makes possible a valuable new perspective on experimental results, and provides a framework for discussion of the concepts behind different algorithm-design approaches. We review a selection of modern algorithms for the purpose of illustrating the distinctions made by the taxonomy. We present the results of a numerical experiment which examined the performance of a number of representative methods on both synthetic and real-world data sets with and without concept drift, and discuss the implications for the directions of future research in light of the taxonomy. On the basis of the experimental results, we are able to give recommendations for the experimental evaluation of algorithms which may be proposed in the future.
PB Elsevier
SN 0925-2312
YR 2018
FD 2018-04
LK http://hdl.handle.net/10259/4757
UL http://hdl.handle.net/10259/4757
LA eng
NO project RPG-2015-188 funded by The Leverhulme Trust, UK, and TIN 2015-67534-P from the Spanish Ministry of Economy and Competitiveness. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 731593.
DS Repositorio Institucional de la Universidad de Burgos
RD 18-abr-2024